Changes in debrisoquine hydroxylation capacity following liver surgery

Addressing phenoconversion: the Achilles' heel of personalized medicine

Phenoconversion is a phenomenon that converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, thereby modifying their clinical response to that of genotypic PMs. Phenoconversion, usually resulting from nongenetic extrinsic factors, has a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies and personalizing therapy in routine clinical practice. The high phenotypic variability or genotype-phenotype mismatch, frequently observed due to phenoconversion within the genotypic EM population, means that the real number of phenotypic PM subjects may be greater than predicted from their genotype alone, because many genotypic EMs would be phenotypically PMs. If the phenoconverted population with genotype-phenotype mismatch, most extensively studied for CYP2D6, is as large as the evidence suggests, there is a real risk that genotype-focused association studies, typically correlating only the genotype with clinical outcomes, may miss clinically strong pharmacogenetic associations, thus compromising any potential for advancing the prospects of personalized medicine. This review focuses primarily on co-medication-induced phenoconversion and discusses potential approaches to rectify some of the current shortcomings. It advocates routine phenotyping of subjects in genotype-focused association studies and proposes a new nomenclature to categorize study populations. Even with strong and reliable data associating patients' genotypes with clinical outcome(s), there are problems clinically in applying this knowledge into routine pharmacotherapy because of potential genotype-phenotype mismatch. Drug-induced phenoconversion during routine clinical practice remains a major public health issue. Therefore, the principal challenges facing personalized medicine, which need to be addressed, include identification of the following factors: (i) drugs that are susceptible to phenoconversion; (ii) co-medications that can cause phenoconversion; and (iii) dosage amendments that need to be applied during and following phenoconversion.

Inflammation-induced phenoconversion of polymorphic drug metabolizing enzymes: hypothesis with implications for personalized medicine

Phenoconversion transiently converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, potentially with corresponding changes in clinical response. This phenomenon, typically resulting from coadministration of medications that inhibit certain drug metabolizing enzymes (DMEs), is especially well documented for enzymes of the cytochrome P450 family. Nonclinical evidence gathered over the last two decades also strongly implicates elevated levels of some proinflammatory cytokines, released during inflammation, in down-regulation of drug metabolism, especially by certain DMEs of the P450 family, thereby potentially causing transient phenoconversion. Clinically, phenoconversion of NAT2, CYP2C19, and CYP2D6 has been documented in inflammatory conditions associated with elevated cytokines, such as human immunodeficiency virus infection, cancer, and liver disease. The potential of other inflammatory conditions to cause phenoconversion has not been studied but experimental and anecdotal clinical evidence supports infection-induced down-regulation of CYP1A2, CYP3A4, and CYP2C9 as well. Collectively, the evidence supports a hypothesis that certain inflammatory conditions associated with elevated proinflammatory cytokines may cause phenoconversion of certain DMEs. Since inflammatory conditions associated with elevated levels of proinflammatory cytokines are highly prevalent, phenoconversion of genotypic EM patients into transient phenotypic PMs may be more frequent than appreciated. Since drug pharmacokinetics, and therefore the clinical response, is influenced by DME phenotype rather than genotype per se, phenoconversion (whatever its cause) can have a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies. There is a risk that focusing on genotype alone may miss important associations between clinical outcomes and DME phenotypes, thus compromising future prospects of personalized medicine.